We have been increasingly feeling the abnormality of daily weather in recent years: severe natural disasters, caused by unprecedented torrential rain and strong winds, have been occurring frequently, as well as extreme weather events such as heat waves (on the one hand,) and heavy snowfall (on the other hand).

It has been pointed out that part of these changes in weather and climate may be attributed to the global environmental change such as global warming. It is not easy, however, to predict the extreme events that have never been observed in the past and to prepare for disasters and changes in daily life.

We, the Department of Seamless Environmental Prediction Research, address the research and development on atmosphere-ocean coupled global cloud-system-resolving model that can predict events on extensive spatiotemporal scales ranging from cloud system causing localized torrential rain, to El Niño phenomena affecting global extreme weather events. We also address the research and development on downscaling technology to generate future projection information about finer-scale local climate change.

Furthermore, we aim to establish a platform for generating and providing seamless environmental prediction information, which would quickly meet the needs of current and future societies, through verifying and upgrading the prediction model systems using observational data and elementary process resolving models. It is also important to elucidate the cloud-precipitation process with multiple structure, which potentially plays a key role to improve reliability in prediction.